About

Professional Summary

AI Engineer and Full-Stack Developer with 4+ years building production systems at the intersection of machine learning and scalable web architecture. Currently specializing in Reinforcement Learning from Human Feedback (RLHF) for large language models, with hands-on experience optimizing AI systems for OpenAI, Turing, and ScaleAI. Dual-degree candidate in Computer Science and Data Science from IIT Madras. Proven track record leading technical communities and delivering end-to-end solutions from concept to deployment.

The Polymath Approach

Artificial Intelligence

RLHF, LLM optimization, generative systems, and AI infrastructure.

Web Systems

Full-stack development, scalable architectures, and modern frameworks.

Data & Systems

Data engineering, analytics pipelines, and system design.

Leadership

Technical community building, strategic planning, and team mentorship.

Current Focus

RLHF Systems LLM Infrastructure AI Model Optimization Digital Public Infrastructure

"The best engineers don't just write code—they architect systems that amplify human potential. My work sits at the intersection of technical rigor and human-centered design."

My Story

I started with a simple curiosity: how do you build systems that actually work for people? That question led me from writing my first Python script to optimizing large language models for some of the biggest names in AI.

The dual-degree path—Computer Science at LNCTS and Data Science at IIT Madras—gave me two lenses: the practical craft of software engineering and the theoretical depth of statistical learning. I don't see these as separate tracks. Every AI system needs solid infrastructure. Every web application can be made smarter with the right models.

Today, I split my time between RLHF work for enterprise clients, building products that solve real problems, and growing technical communities. The through-line? Systems thinking—whether it's a neural network architecture or a community of 500+ developers.